CBIR使用RGB颜色纹理的纹理

Sudhakar Putheti, S. Edara, Sai Alekya Edara
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引用次数: 1

摘要

本文的目的是在低计算复杂度的情况下提高CBIR系统的成功率。CBIR系统的成功率取决于被检索图像的定位。这可以通过使用描述形状的图像的R, G, B平面的纹理来实现。本文提出了计算复杂度较低的3 × 3网格来提取文本。该方法基于从图像的R、G、B通道提取的文本的texels(低级特征),因为颜色变化也可以提供形状信息。在Corel数据库中使用1000多张自然图像对该方法进行了测试。结果表明,该方法比文本共现矩阵法、文本多直方图法更有效。与TCM和TMH方法相比,该方法对颜色、纹理和形状特征具有较好的识别能力。
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CBIR using texels of RGB colour textons
The aim of this paper is to increase the success rate of CBIR system with low computational complexity. The success rate of CBIR system depends on localization of the image to be retrieved. This can be achieved by using textons of R, G, B planes of the image which describes the shape. This paper proposes 3 × 3 grids to extract the textons with low computational complexity. The proposed method is based on the texels (low level features) of textons extracted from R,G,B channels of an image as chromatic changes also give shape information. The proposed method is tested on Corel database with more than 1000 natural images. The results demonstrate that it is more efficient than texton co-occurrence matrix, texton multi histogram methods. It has good discrimination power of color, texture and shape features when compared to that of TCM and TMH methods.
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